US 6861979 B1 Abstract A method and apparatus for detecting and correcting anomalous measurements in a satellite navigation receiver is disclosed. Anomalous measurements are detected using the redundancy of observed satellite signals, or by analyzing the relationship between phase measurements at two frequencies when using dual frequency receivers. Upon determination that an anomalous measurement exists, the particular channel on which the anomalous measurement has occurred is determined. In addition, the extent of the anomalous measurement is estimated to produce an estimated error value. This information may then be used by the satellite navigation receiver in order to increase the accuracy of a navigation task.
Claims(56) 1. A method for detecting anomalous phase measurements in a satellite differential navigation system in which a first satellite receiver and a second satellite receiver each compute phase measurements on a plurality of satellite channels, said method comprising the steps, performed for each of a plurality of iterations, of:
a) generating a combined phase difference vector;
b) generating a phase mismatch vector representing the difference between said combined phase difference vector and an estimated combined phase difference vector;
c) generating an averaged estimate vector representing the averaged estimate of said phase mismatch vector over said channels;
d) generating a residual vector representing the difference between said phase mismatch vector and said averaged estimate vector;
e) generating a vector of controlling signals by linear transformation of said residual vector and said averaged estimate vector;
f) generating said estimated combined phase difference vector by successively storing components of said vector of controlling signals for each of said channels; and
g) detecting anomalous phase measurements by analyzing said residual vector.
2. The method of
_{l }. . . Φc_{j }. . . Φc_{N}) for a j-th satellite channel, and wherein step a) of generating a combined phase difference vector further comprises the step of:
calculating said phase difference vector Φc as Φc=Φ
^{B}−Φ^{R }where vector Φ^{B }comprises the full phases measured by one of said satellite receivers for each j-th satellite channel (Φ_{Bl }. . . Φ_{Bj }. . . Φ_{BN}) and vector Φ^{R }comprises the fall phases measured by the other satellite receiver for each j-th satellite channel (Φ_{Rl }. . . Φ_{Rj }. . . Φ_{RN}). 3. The method of
_{1 }. . . Φc_{j }. . . Φc_{N}) for a j-th satellite channel, and wherein step a) of generating a combined phase difference vector further comprises the step of:
calculating said phase differences Φc
_{j }of said phase difference vector Φc as
Φ c _{1}=(Φ^{B} _{2j}−Φ^{R} _{2j})−(Φ^{B} _{1j}−Φ^{R} _{1j})(f2/f1) where Φ
^{B} _{2j }and Φ^{B} _{1j }represent the full phase measured by one of the satellite receivers at each j-th satellite channel at frequencies f2 and f1 respectively, andwhere Φ
^{R} _{2j }and Φ^{R} _{1j }represent the full phase measured by the other of the satellite receivers at each j-th satellite channel at frequencies f2 and f1 respectively.4. The method of
calculating said average estimate vector ΔΨ as
where ΔΦc
_{j }represents the components of said phase mismatch vector for a j-th satellite channel, w_{j }represents a weight coefficient for each j-th satellite channel, and N represents the number of satellite channels.5. The method of
calculating said average estimate vector ΔΨ as ΔΨ=H·G·ΔΦc where H is a matrix of directional cosines, ΔΦc represents said phase mismatch vector, and G is a matrix defined by G=(H
^{T}R^{−1}H)^{−1}H^{T}R^{−1 }where R is a covariance matrix of phase mismatches. 6. The method of
generating said vector of controlling signals in combined loop filters of each of said plurality of channels.
7. The method of
_{cj}) for a j-th channel according to the following:
where V
_{prj}(i) is a predicted value computed on the basis of a priori data, and α, β, γ are coefficients of the loop filter.8. The method of
9. The method of
10. The method of
h) comparing residuals of said residual vector with a threshold, and
i) determining that a particular channel has an anomalous phase measurement if a residual associated with said particular channel exceeds said threshold.
11. The method of
12. The method of
j) eliminating said particular channel from subsequent iterations of step a); and
repeating steps b) through j) until no residual exceeds said threshold or until a threshold number of said channels remain.
13. The method of
h) generating a weighted sum of residual squares for said channels;
i) comparing said weighted sum of residual squares to a threshold; and
j) determining that an anomalous phase measurement exists if said weighted sum of residual squares exceeds said threshold.
14. The method of
k) determining that a particular channel has an anomalous phase measurement if a residual associated with said particular channel is the maximum residual in said residual vector.
15. The method of
l) eliminating said particular channel from subsequent iterations of step a); and
repeating steps b) through l) until said weighted sum of residual squares does not exceed said threshold or until a threshold number of said channels remain.
16. The method of
k) eliminating x channels from subsequent iterations of step a), varying the channels eliminated for each iteration of step k); and
repeating steps b) through k) until either said weighted sum of residual squares does not exceed said threshold or until x reaches a threshold, incrementing x by one after all combinations of channels for a given x have been eliminated during an iteration of step k).
17. The method of
18. The method of
19. The method of
h) using information about said anomalous phase measurements detected in step g) in a navigation task.
20. The method of
i) generating a cycle slip estimate for a channel determined to have an anomalous phase measurement and using said cycle slip estimate in said navigation task.
21. An apparatus for detecting anomalous phase measurements in a satellite differential navigation system in which a first satellite receiver and a second satellite receiver each compute phase measurements on a plurality of satellite channels, said apparatus comprising:
a combined phase difference generator for generating a combined phase difference vector;
means for generating a phase mismatch vector representing the difference between said combined phase difference vector and an estimated combined phase difference vector;
an integrated discriminator for generating an averaged estimate vector representing the averaged estimate of said phase mismatch vector over said channels;
means for generating a residual vector representing the difference between said phase mismatch vector and said averaged estimate vector;
at least one joint loop filter for generating a vector of controlling signals by linear transformation of said residual vector and said averaged estimate vector;
an accumulator for generating said estimated combined phase difference vector by successively storing components of said vector of controlling signals for each of said channels; and
a residuals analyzer for detecting anomalous phase measurements by analyzing said residual vector.
22. The apparatus of
_{l }. . . Φc_{j }. . . Φc_{N}) for a j-th satellite channel, and wherein said phase difference generator generates said combined phase difference vector Φc as Φc=Φ^{B}−Φ^{R }where vector Φ^{B }comprises the full phases measured by one of said satellite receivers for each j-th satellite channel (Φ_{Bl }. . . Φ_{Bj }. . . Φ_{BN}) and vector Φ^{R }comprises the full phases measured by the other satellite receiver for each j-th satellite channel (Φ_{Rl }. . . Φ_{Rj }. . . Φ_{RN}).23. The apparatus of
_{l }. . . Φc_{j }. . . Φc_{N}) for a j-th satellite channel, and wherein said phase difference generator generates said phase differences Φc_{j }of said phase difference vector Φc as
Φ c _{j}=(Φ^{B} _{2j}−Φ^{R} _{2j})−(Φ^{B} _{1j}−Φ^{R} _{1j})(f2/f2) where Φ
^{B} _{2j }and Φ^{B} _{1j }represent the full phase measured by one of the satellite receivers at each j-th satellite channel at frequencies f2 and f1 respectively, andwhere Φ
^{R} _{2j }and Φ^{R} _{1j }represent the full phase measured by the other of the satellite receivers at each j-th satellite channel at frequencies f2 and f1 respectively.24. The apparatus of
where ΔΦc
_{j }represents the components of said phase mismatch vector for a j-th satellite channel, w_{j }represents a weight coefficient for each j-th satellite channel, and N represents the number of satellite channels.25. The apparatus of
^{T}R^{−1}H)^{−1}H^{T}R^{−1 }where R is a covariance matrix of phase mismatches.26. The apparatus of
27. The apparatus of
_{cj}) for a j-th channel according to the following:
where V
_{prj}(i) is a predicted value computed on the basis of a priori data, and α, β, γ are coefficients of the loop filter.28. The apparatus of
29. The apparatus of
30. The apparatus of
31. The apparatus of
32. The apparatus of
33. A method for detecting anomalous phase measurements in a satellite differential navigation system in which a first satellite receiver and a second satellite receiver each compute phase measurements on a plurality of satellite channels, said method comprising the steps, performed for each of a plurality of iterations, of:
a) generating a combined phase difference vector;
b) generating an increment vector representing the difference between said combined phase difference vector and a combined phase difference vector of a preceding iteration,
c) generating an averaged increment estimate vector representing the averaged estimate of said increment vector;
d) generating an incremental residual vector representing the difference between said increment vector and said averaged increment estimate vector;
e) generating an integrated residual vector from said incremental residual vector; and
f) detecting anomalous phase measurements by analyzing said integrated residual vector.
34. The method of
calculating said phase difference vector Φc(i) as Φc(i)=Φ
^{B}(i)−Φ^{R}(i)−Φ^{BR}(i) where vector Φ^{B}(i) comprises the full phases measured by one of said satellite receivers for each i-th iteration and vector Φ^{R}(i) comprises the full phases measured by the other satellite receiver for each i-th iteration and Φ^{BR}(i) is a prediction of satellite movement. 35. The method of
calculating said average estimate vector Δ{circumflex over (Φ)} as
Δ{circumflex over (Φ)}( i)=H(i)·G(i)·ΔΦc(i), where Δ{circumflex over (Φ)}(i) represents the components of said average estimate vector for an i-th iteration, H is a matrix of directional cosines, G is a matrix defined by G=(H
^{T}R^{−1}H)^{−1}H^{T}R^{−1 }where R is a covariance matrix of phase mismatches, and ΔΦc(i)=Φc(i)−Φc(i−1) where Φc(i) is a vector of combined phase difference at each i-th iteration.36. The method of
δ( i)=A·δ(i−1)+Δδ(i) for each i-th iteration, where A is a coefficient in the range 0.995 . . . 0.999.
37. The method of
g) generating a weighted sum of integrated residual squares for said channels;
h) comparing said weighted sum of integrated residual squares to a threshold; and
i) determining that an anomalous phase measurement exists if said weighted sum of integrated residual squares exceeds said threshold.
38. The method of
j) eliminating x channels from subsequent iterations of step a), varying the channels eliminated for each iteration of step j); and
repeating steps b) through j) until either said weighted sum of integrated residual squares does not exceed said threshold or until x reaches a threshold, incrementing x by one after all combinations of channels for a given x have been eliminated during an iteration of step j).
39. The method of
40. The method of
41. The method of
g) using information about said anomalous phase measurements detected in step f) in a navigation task.
42. The method of
h) generating a cycle slip estimate for a channel determined to have an anomalous phase measurement and using said cycle slip estimate in said navigation task.
43. The method of
g) receiving channel indicator alarms from a channel indicator, said channel indicator alarms marking channels with anomalous phase measurements;
h) eliminating channels marked with channel indicator alarms from subsequent iterations of step a); and
i) repeating steps a) through f).
44. The method of
j) generating a weighted sum of integrated residual squares for said channels;
k) comparing said weighted sum of integrated residual squares to a threshold; and
l) determining that an anomalous phase measurement exists if said weighted sum of integrated residual squares exceeds said threshold.
45. An apparatus for detecting anomalous phase measurements in a satellite differential navigation system in which a first satellite receiver and a second satellite receiver each compute phase measurements on a plurality of satellite channels, said apparatus comprising:
a) a combined phase difference generator for generating a combined phase difference vector;
b) means for generating an increment vector representing the difference between said combined phase difference vector and a combined phase difference vector of a preceding measurement,
c) an integrated converter for generating an averaged increment estimate vector representing the averaged estimate of said increment vector;
d) means for generating an incremental residual vector representing the difference between said increment vector and said averaged increment estimate vector,
e) a digital filter for generating an integrated residual vector from said incremental residual vector; and
f) a residuals analyzer for detecting anomalous phase measurements by analyzing said integrated residual vector.
46. The apparatus of
^{B}(i)−Φ^{R}(i)−Φ^{BR}(i) where vector Φ^{B}(i) comprises the full phases measured by one of said satellite receivers for each i-th iteration and vector Φ^{R}(i) comprises the full phases measured by the other satellite receiver for each i-th iteration and Φ^{BR}(i) is a prediction of satellite movement.47. The apparatus of
Δ{circumflex over (Φ)}( i)=H(i)·G(i)·ΔΦc(i), where Δ{circumflex over (Φ)}(i) represents the components of said average estimate vector for an i-th iteration, H is a matrix of directional cosines, G is a matrix defined by G=(H
^{T}R^{−1}H)^{−1}H^{T}R^{−1 }where R is a covariance matrix of phase mismatches, and ΔΦc(i)=Φc(i)−Φc(i−1) where Φc(i) is a vector of combined phase difference at each i-th iteration.48. The apparatus of
49. The apparatus of
δ( i)=A·δ(i−1)+Δδ(i) for each of an i-th iteration, where A is a coefficient in the range 0.995 . . . 0.999.
50. A method for detecting anomalous phase measurements in a satellite differential navigation system in which a first satellite receiver and a second satellite receiver each compute phase measurements on a plurality of satellite channels, said method comprising the steps, performed for each of a plurality of iterations, of:
a) generating a combined phase difference vector;
b) generating an increment vector representing the difference between said combined phase difference vector and a combined phase difference vector of an initial measurement at an initial time,
c) generating a corrected increment vector using a cycle slip correction estimate generated in a preceding iteration;
d) analyzing channel indicator alarms;
e) generating an averaged increment estimate vector representing the averaged estimate of said corrected increment vector using channels not associated with a channel indicator alarm;
f) generating a residual vector representing the difference between the corrected increment vector and the averaged increment estimate vector; and
g) generating said cycle slip correction estimate using said residual vector.
51. The method of
including a prediction of phase difference in said difference.
52. The method of
53. The method of
h) using said cycle slip correction estimate in a navigation task.
54. An apparatus for detecting anomalous phase measurements in a satellite differential navigation system in which a first satellite receiver and a second satellite receiver each compute phase measurements on a plurality of satellite channels, said apparatus comprising:
a) a combined phase difference generator for generating a combined phase difference vector;
b) means for generating an increment vector representing the difference between said combined phase difference vector and a combined phase difference vector of an initial measurement at an initial time;
c) a cycle slip correction unit for generating a cycle slip correction estimate;
d) means for generating a corrected increment vector using a cycle slip correction estimate generated in a preceding measurement;
d) a channel indicator analyzer for analyzing channel indicator alarms;
e) an integrated converter for generating an averaged increment estimate vector representing the averaged estimate of said corrected increment vector using channels not associated with a channel indicator alarm;
f) means for generating a residual vector representing the difference between the corrected increment vector and the averaged increment estimate vector; and
g) a correction unit for generating said cycle slip correction estimates using said residual vector.
55. The apparatus of
56. The apparatus of
Description This application claims the benefit of U.S. Provisional Application No. 60/536,872, filed Jan. 16, 2004. This invention relates generally to satellite navigation receivers and more particularly to the detection and correction of anomalous measurements in a satellite navigation receiver. Satellite navigation systems, such as GPS (USA) and GLONASS (Russia), are well known in the art and are intended for highly accurate self-positioning of users possessing special navigation receivers. A navigation receiver receives and processes radio signals transmitted by satellites located within line-of-sight distance of the receivers. The satellite signals comprise carrier signals that are modulated by pseudo-random binary codes. The receiver measures the time delay of the received signal relative to a local reference clock or oscillator. These measurements enable the receiver to determine the so-called pseudo-ranges between the receiver and the satellites. The pseudo-ranges are different from the ranges (distances) between the receiver and the satellites due to various noise sources and variations in the time scales of the satellites and receiver. If the number of satellites is large enough, then the measured pseudo-ranges can be processed to determine the user location and coordinate time scales. The requirement of accurately determining user location with a high degree of precision, and the desire to improve the stability and reliability of measurements, have led to the development of differential navigation (DN). In differential navigation, the task of finding the user position, also called the Rover, is performed relative to a Base station (Base). The precise coordinates of the Base station are known and the Base station is generally stationary during measurements. The Base station has a navigation receiver which receives and processes the signals of the satellites to generate measurements. These signal measurements are transmitted to the Rover via a communication channel (e.g., wireless). The Rover uses these measurements received from the Base, along with its own measurements taken with its own navigation receiver, in order to precisely determine its location. The location determination is improved in the differential navigation mode because the Rover is able to use the Base station measurements in order to compensate for the major part of the strongly correlated errors in the Rover measurements. Various modes of operation are possible while using differential navigation. In post-processing (PP) mode, the Rover's coordinates are determined by co-processing the Base and Rover measurements after all measurements have been completed. This allows for highly accurate location determination because more data is available for the location determination. In real-time processing (RTP) mode, the Rover's coordinates are determined in real time upon receipt of the Base station information received via the communication channel. The location determination accuracy of differential navigation may be further improved by supplementing the pseudo-range measurements with measurements of the phases of the satellite carrier signals. If the carrier phase of the signal received from a satellite in the Base receiver is measured and compared to the carrier phase of the same satellite measured in the Rover receiver, measurement accuracy may be obtained to within several percent of the carrier's wavelength. The practical implementation of those advantages, which might otherwise be guaranteed by the measurement of the carrier phases, runs into the problem of ambiguity resolution for phase measurements. The ambiguities are caused by two factors. First, the difference of distances from any satellite to the Base and Rover is usually much greater than the carrier's wavelength. Therefore, the difference in the phase delays of a carrier signal received by the Base and Rover receivers may substantially exceed one cycle. Second, it is not possible to measure the integer number of cycles from the incoming satellite signals; one can only measure the fractional part. Therefore, it is necessary to determine the integer number of cycles, which is called the “ambiguity”. More precisely, we need to determine the set of all such integer parts for all the satellites being tracked, one integer part for each satellite. One has to determine this set along with other unknown values, which include the Rover's coordinates and the variations in the time scales. At a high level, the task of generating highly-accurate navigation measurements is formulated as follows: it is necessary to determine the state vector of a system, with the vector containing n Two sets of navigation parameters are measured by the Base and Rover receivers, respectively, and are used to determine the unknown state vector. Each set of parameters includes the pseudo-range of each satellite to the receiver, and the full (complete) phase of each satellite carrier signal. Each pseudo-range is obtained by measuring the time delay of a code modulation signal of the corresponding satellite. The code modulation signal is tracked by a delay-lock loop (DLL) circuit in each satellite tracking channel. The full phase of a satellite's carrier signal is tracked by a phase-lock-loop (PLL) in the corresponding satellite tracking channel. An observation vector is generated as the collection of the measured navigation parameters for specific (definite) moments of time. The relationship between the state vector and the observation vector is defined by a well-known system of navigation equations. Given an observation vector, the system of equations may be solved to find the state vector if the number of equations equals or exceeds the number of unknowns in the state vector. Conventional statistical methods are used to solve the system of equations: the least squares method, the method of dynamic Kalman filtering, and various modifications of these methods. Practical implementations of these methods in digital form may vary widely. In implementing or developing such a method on a processor, one usually must find a compromise between the accuracy of the results and speed of obtaining results for a given amount of processor capability, while not exceeding a certain amount of loading on the processor. One general scheme comprises the following steps. The measured values of the pseudo-ranges and full phases at specific (definite) moments of time, along with an indication of the satellites to which these measurements belong and the time moments of the measurements, are transmitted from the Base to the Rover. Corresponding values are measured in the Rover receiver. The processing includes the determination of the single differences of the pseudo-ranges and full phases between the Base and Rover measurements for each satellite. The strongly correlated errors are compensated (i.e., substantially cancelled) in the single differences. Then, the residuals of the single differences are calculated by subtraction of calculated values from the measured results. The processing of residuals allows one to linearize the initial system of navigation equations (sometimes several subsequent iterations are necessary), which makes possible the use of the well developed body of mathematics for solving systems of linear equations. The components of the state vector, with the n ambiguities included, are found as a result of the solution. But the calculated values of the ambiguities are not necessarily integer numbers, and are often floating point numbers. Because of this, they are called float ambiguities, or floating ambiguities, at this stage of the solution. To find true values of the integer ambiguities one uses the procedure of rounding off the float ambiguity vector to the nearest set of integers. This process is called the ambiguity resolution. Only after the ambiguity resolution has been done is it possible to determine the true values of residuals and then, by solving the system of equations again, to find the coordinate values for the baseline connecting the Base and Rover, and consequently to determine the exact coordinates of the Rover and the correction to its clock drift. The above described general scheme of computations is well known in the art and is described in further detail, for example, in, Bradford W. Parkinson and James J. Spilker Jr., In most cases the Rover receiver operates in a complicated environment in which various external influences cause measurement errors. For example, external signals may interfere with the satellite signals, and structures and terrain may result in multipath errors. We distinguish now between two types of errors, normal errors and abnormal errors. Normal errors are normally distributed white noise errors which may be compensated for during the location calculation. Abnormal errors are large systematic errors which may prevent the system from calculating an accurate location. Such abnormal errors are rarely a consequence of occasional spikes of intrinsic noise. More often, they are the result of severe exposure of the receiver. For example, strong reflected signals that interfere with the direct satellite signal would cause an abnormal error. Similarly, extreme radio interference may also result in abnormal errors. Partial or complete shading of the Rover receiver may also result in errors due to radio wave diffraction. If the shading is partial and minor, the measurement error may be minimal. However, if a satellite is completely shaded (i.e., blocked), all that remains is the multipath signal. As a result, tracking in the channel is interrupted and the measured phase is lost resulting in an abnormal error. Dynamic effects on the receiver (i.e., certain motion of the Rover) may also cause abnormal errors. Impulse accelerations impact both the receiving antenna and the quartz of the local reference oscillator resulting in drift of the intermediate carrier frequency and measured phase. One specific type of abnormal error is a PLL cycle slip which is a cycle slip in the PLL circuits which are tracking the satellite carrier signal. After a cycle slip occurs, the PLL circuit transits to a new point of steady balance, after which it goes on with tracking the satellite carrier signal. As a result of a cycle slip, an abnormal error equal to several integer number of semi-cycles (half-cycles) is introduced into the full phase measurements. A cycle slip is characterized by two parameters, value and duration. The slip's value (in cycles) is determined by either 0.5K or K dependent on the PLL discriminator's type, where K is a random integer number. The duration of the cycle slip is also random. Minimal duration is defined by the PLL band while maximal duration depends upon the cause bringing about the cycle slip and can last up to several seconds. When the duration is long enough, tracking is lost. There are various known techniques for detecting and correcting for cycle slip. For example, U.S. Pat. No. 5,502,641 discloses a method of detecting and correcting cycle slips caused by short-term blocking of satellite signals using phase extrapolation. In addition, S. Bisnath, D. Kim, and R. B. Langley, The present invention provides an improved method and apparatus for detecting anomalous phase measurements in a satellite differential navigation system. In accordance with one embodiment of the invention, a feedback loop is utilized to detect the anomalous measurements. In this embodiment, a phase difference vector is generated using the phase of the satellite signals as received at each of two satellite receivers. If the satellite receivers are single frequency receivers, then the phase difference vector generally represents the difference in phase as measured at each of the two satellite receivers. If the satellite receivers are dual frequency receivers, then the phase difference vector may be calculated using the difference in phase as measured at each of the two satellite receivers and further based on the relationship between the two frequencies. A phase mismatch vector is then generated, which represents the difference between the combined phase difference vector and an estimated combined phase difference vector. An averaged estimate vector representing the averaged estimate of the phase mismatch vector is generated. Next, a residual vector representing the difference between the phase mismatch vector and the averaged estimate vector is generated. A linear transformation of the residual vector and the averaged estimate vector provides a vector of controlling signals. Then, an estimated combined phase difference vector is generated by successively storing components of the vector of controlling signals for each of the satellite channels. Anomalous phase measurements are then detected by analyzing the residual vector. The invention provides various techniques for analyzing the residual vector and therefore detecting anomalous phase measurements. In one embodiment, the anomalous phase measurements are detected by comparing residuals of the residual vector with a threshold and determining that a particular channel has an anomalous phase measurement if a residual associated with the particular channel exceeds the threshold. Once such a particular channel is found, further checking may be performed by eliminating that channel from further calculations of the phase difference vector and repeating the remaining steps until no residual exceeds the threshold, or until a threshold number of channels remain. Alternatively, anomalous phase measurements may be detected by generating a weighted sum of residual squares for the channels, comparing that weighted sum to a threshold, and determining that an anomalous phase measurement exists if the weighted sum exceeds the threshold. In accordance with this technique, the particular channel having the maximum residual may be considered as a channel having an anomalous phase measurement. Again, the identification of the particular channel may be checked by eliminating the channel from subsequent calculations of the phase difference vector and repeating the remaining steps until the weighted sum of residual squares does not exceed the threshold or until a threshold number of channels remain. Upon identification of an anomalous phase measurement, the information about the anomalous phase measurement may be used by a satellite navigation receiver in order to increase the accuracy of a navigation task. In addition, a cycle slip estimate for a channel determined to have an anomalous phase measurement may be computed, and such cycle slip estimate may also be used in the navigation task. In accordance with an another embodiment of the invention, anomalous phase measurements are detected using phase increments in adjacent measurements and without the feedback circuit of the first embodiment. In this embodiment, a combined phase difference vector is generated using the phase of the satellite signals as received at each of two satellite receivers. An increment vector is then generated, which represents the difference between the combined phase difference vector and the combined phase difference vector of a preceding iteration. An averaged increment estimate vector representing the averaged estimate of the increment vector is generated. Next, an incremental residual vector representing the difference between the increment vector and the averaged increment estimate vector is generated. An integrated residual vector is then generated from the incremental residual vector. Anomalous phase measurements are then detected by analyzing the integrated residual vector. In accordance with yet another embodiment of the invention, anomalous phase measurements are detected based upon readings from channel indicators which are sensitive to sharp changes of signal amplitude or phase. Alarm signals associated with these channel indicators may indicate a significant probability of an anomalous measurement. In this embodiment, a combined phase difference vector is generated using the phase of the satellite signals as received at each of two satellite receivers. An increment vector is then generated, which represents the difference between the combined phase difference vector and the combined phase difference vector of an initial measurement. A corrected increment vector is then generated using a cycle slip correction estimate generated in a preceding iteration. Channel indicator alarms are analyzed and an averages increment estimate vector representing the averaged estimate of the corrected increment vector is generated using channels not associated with a channel indicator alarm. Next, a residual vector representing the difference between the corrected increment vector and the averaged increment estimate vector is generated. A cycle slip correction estimate is then generated using the residual vector. These and other advantages of the invention will be apparent to those of ordinary skill in the art by reference to the following detailed description and the accompanying drawings. As described above in the Background of the Invention, one of the problems with satellite navigation systems is the PLL cycle slip. In accordance one embodiment of the present invention, the Rover unit We note here that the term receiver is used in referring to both the GPS satellite receiver unit Prior to a detailed description of the anomaly indicator module, a high level description of the overall functions performed by the anomaly indicator module will be given. The anomaly indicator module performs the following functions. The first function of the anomaly indicator module is to detect the existence of an anomalous measurement in the satellite receiver. In performing this function, the redundancy of observed satellite signals is used. As is well known, in order to determine the location of the Rover, the Rover must receive signals from at least four satellites. Signals received from additional satellites in excess of four are redundant signals which are useful in the detection of anomalous measurements. We will therefore assume that the number of satellites observed simultaneously at the Base and Rover includes redundant satellites. As such, the phase measured in a particular satellite channel can be compared with an estimate of the phase obtained using other channel measurements. If the phase measurement of the particular satellite channel does not contain an abnormal error, then the difference between the measured phase and the estimated phase will not be too large. By establishing an appropriate threshold of acceptable difference, abnormal or anomalous phase measurements can be detected. The redundancy of satellite signals may also be used by measuring the variance of phase measurements of the different channels relative to a mean estimate of all the channels and comparing this variance to a threshold. If the measured variance is greater than a permissible threshold, then an anomalous measurement is detected. Another technique for detecting an anomalous measurement may be used when a dual frequency receiver measures phase at two different frequencies, for example the L Another technique for detecting an anomalous measurement is to use empiric data which indicates that an anomalous error may have been caused by a strong external influences on the satellite receiver. For example, such external influences may include signal shading or fading, and motion of the satellite receiver. As described above, such motion may affect the effectiveness of the antenna. Such motion may also affect the quartz of the reference oscillator in the satellite receiver. Such external influences may be tracked by special channel indicators sensitive to sharp changes of signal amplitude or phase. Alarm signals associated with these channel indicators may indicate a significant probability of an anomalous measurement. Another function of the anomaly indicator module is to determine the particular channel on which the anomalous measurement has occurred. While some of the techniques described above for detecting that an anomalous measurement exists will also identify the particular channel on which it occurred, others of the techniques will not identify the particular channel on which the anomalous measurement has occurred. For example, the use of channel indicator alarms will identify the particular channel on which the anomalous measurement has occurred. However, consider the above described technique of comparing the measured variance relative to the mean estimate with a threshold. An anomaly detected in this manner suggests the particular channel on which the anomaly occurred because of the deviation of the particular channel's measurement from the mean. However, it is useful to perform another check on the identified channel. The verification is carried out by eliminating the suspected channel in the calculation of the mean. If, as a result of this elimination, the variance is reduced and is less than the threshold then the anomalous measurement is assumed to be found. Alternatively, if, as a result of the elimination, the variance is not less than the threshold, then the identified channel is unlikely the channel with the anomalous measurement. In this case, another likely candidate channel is eliminated. This other likely candidate channel may be chosen as the channel with the next largest deviation from the mean. Upon replacing the candidate channel, in various embodiments the originally excluded channel may either be restored into the calculation of the mean or it may remain excluded. This technique may be repeated until the channel with the anomalous measurement is found. Another function of the anomaly module is to estimate an error value which represents the extent of the anomalous measurement. Knowledge of the extent of the error may be useful in increasing the accuracy of the location function of the satellite receiver. Appropriate corrections may be provided from the anomaly indicator module Again, referring to the error detection technique of comparing the measured variance with the threshold, if the channel with the anomalous measurement has been found and removed from the computation of the mean, then the deviation of the channel's measurement from the mean can be considered as an estimate of the abnormal error on that channel. However, in the general case, such an estimate is generally not useful in determining corrections because it does not contain any new information and does not increase navigation location determining accuracy compared with simply removing that channel from the location determination. Anomalous error due to cycle slip, however, is an exception to the general case. After a cycle slip, the channel PLL continues tracking in normal mode. Since the cycle slip error is known to be a discrete value equal to an integer number of semi-cycles, the deviation of the measurement of the anomalous channel from the mean may be very useful. Having provided an overview of the functioning of the anomaly indicator module, further details of the functioning of the anomaly indicator module will now be provided. Prior to a description of the further details, we will provide an introduction to the nomenclature used. We use subscript j to indicate a channel number, where j is either within limits from 1 to N where N is the full number of actual satellite channels or within limits from 1 to n<N where n is the number of satellite channels left after eliminating the channels with anomalous measurements. The symbol i is used in brackets on the right to indicate the number of discrete time measurements, where i increases by 1 in each successive clock pulse (we note here that in some equations i is omitted for the sake of clarity). Vectors are indicated in bold. We now describe in further detail the several embodiments of an anomaly indicator module in accordance with the principles of the present invention. As represented in block The clock is determined by the time instances when Base measurements are received by the Rover via the communication channel. The time interval (Δt) between adjacent transmitted measurements is generally equal to approximately 0.2-1.0 s. A set of phase combinations is generated each clock from the input data for all the satellite channels by the combined phase difference generator In a dual-frequency receiver the combined phase difference Φc Next, operators The phase mismatches (ΔΦc) of all channels are provided to an integrated discriminator In the case of a moving Rover (operating in so-called kinematic mode) the integrated averaged estimates ΔΨ The residual δ The function of the accumulator If the generalized/integrated averaged estimate ΔΨ is the same for all the channels and is computed as a weighted sum of phase mismatches according to equation (3), then the predicted value V In various embodiment, the coefficients α, β, γ of the loop filter may be selected by various methods. One method is to assume that the coefficients are constant values. Advantageous values for these coefficients are as follows:
Measurement noise is discrete white noise with RMS in the range RMS=0.05 . . . 0.1 cycle. The dynamic model of the process tracked is represented as a result of passing discrete white noise through two serial accumulators with the RMS of initial white noise being selected so that the steady-state band of the Kalman filter is within 0.001 . . . 0.005 Hz. Returning now to First, consider the case where the integrated discriminator A second embodiment of the residual analyzer is based upon verifying the so-called criterion χ A third embodiment of the residual analyzer is also based on criteria χ The three above described embodiments of the residuals analyzer Following the analysis of the residuals, the decision module In addition, the anomaly module can transfer to the navigation location determining module One skilled in the art would recognize that the navigation location determining module We now describe the operation of the channel indicators. The task of the channel indicators is to detect disturbance in the satellite channels that may cause anomalous phase measurements and to mark (i.e., flag) the channels with an alarm. A distinction can be made between amplitude and dynamic disturbances. Amplitude disturbance, for various reasons, results in a considerable reduction of satellite signal amplitude at the input of the receiver. Partial or full shading by any local object may cause amplitude disturbance. Such shading corresponds to changing the measured phase. Full shading follows a semi-shade interval, during which the signal is received only by diffraction. This results in the length of the radio wave becoming longer and the appearance of a large phase change. Full shading causes the PLL to open and the guided/controlled generator changes its phase and frequency due to noise and a reflected signal that comes from a different direction and thereby may be unshaded. Under strong multi-path conditions the interference of direct and reflected signals results in simultaneous amplitude fading and phase fluctuation. Deep amplitude disturbance and corresponding anomalous phase errors are especially noticeable when the Rover is close to urban buildings or among trees. Such errors tend to occur more often in the channels tracking satellites at low elevation. Dynamic disturbance arises as pulse accelerations (i.e., motion) of the moving Rover, which may be caused, for example, by road shocks and vibrations due to nearby equipment. Such accelerations affect the receiver's antenna and the reference oscillator quartz. Motion of the antenna results in a change in the received signal phase. The magnitude of this change is proportional to a double time interval of the scalar multiplication product of two vectors, namely the acceleration vector occurring during the motion/shock and the range-to-satellite vector. It should be noted that the phase change would differ for different satellite channels. The shock of the quartz due to piezoelectric effect results in changing the reference oscillation frequency. The value of this frequency change depends on g-sensitivity of the quartz and the angle between the main quartz's axis and the shock-acceleration vector. Correspondingly, the phase change is proportional to the integral of acceleration and is the same for all satellite channels. Joint action of diverse perturbations and intrinsic noise normally leads to anomalous errors, which, however, do not take place simultaneously in different channels and at various carrier frequencies. In order to detect a perturbation in the channel, the channel indicators analyze quadrature components of the received signal (I,Q). The methods of analysis are known to be dependent on the task being solved. The specific feature of the case under consideration is the fact that false lock is less dangerous than missing. This results from redundancy in the number of satellite channels and the fact that the validity of alarms can be verified by other methods. In addition, the channel indicator does not need to distinguish between amplitude and dynamic perturbations, and there are no strict limitations on the permissible delay of alarm signals. The elimination of the channel in the anomaly indicator module does not necessarily indicate that the channel will be deleted from solving the navigation task, which would bring about reducing the accuracy of coordinate measurements. One embodiment of a channel indicator for use in implementing the present invention consists of two parts, an angle indicator and an amplitude indicator. The angle indicator compares the value Z In amplitude fading Z The angle indicator may miss a perturbation if, during the shading of the satellite, the PLL gradually transits to tracking a weaker reflected signal that has its own Doppler shift and can take the phase far away. Thus, it is expedient to supplement the angle indicator with the amplitude indicator. The amplitude indicator measures value Z As represented in block Channel weight coefficient generator The increments ΔΦc(i) are passed to the integrated converter Operator The next step is to move from increment residuals to integrated residuals. It is necessary to give the anomaly indicator module an opportunity to detect an anomalous error that grows so slowly that its influence on the increment residuals is hidden by noise. Integrated residuals δ(i) are generated by the filter-integrator The residuals analyzer It is also possible to use the χ If the number of channels remaining is not less than four and χ Slip corrections Φc The decision module The foregoing Detailed Description is to be understood as being in every respect illustrative and exemplary, but not restrictive, and the scope of the invention disclosed herein is not to be determined from the Detailed Description, but rather from the claims as interpreted according to the full breadth permitted by the patent laws. It is to be understood that the embodiments shown and described herein are only illustrative of the principles of the present invention and that various modifications may be implemented by those skilled in the art without departing from the scope and spirit of the invention. Patent Citations
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